render_uai_result

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'deterministic' and the output language options, which are useful, but it does not disclose error behavior, the role of expected_context_hash, or any side effects. The description adds some behavioral context but leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states purpose and output languages. It is concise and front-loaded with the primary action, but it is so brief that it omits crucial operational details. It is appropriately sized but slightly under-specified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although an output schema exists, the description lacks parameter semantics, usage guidance, and behavioral caveats, making it incomplete for an agent to correctly invoke the tool. The description does not explain the required context hash or how language selection works, so an agent would have to infer or experiment.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the parameters. It does not mention result_json, expected_context_hash, or the allowed language values beyond the default 'en'. The description provides no semantic information about the parameters, leaving agents without guidance on what to supply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (render), the resource (structured UAI/1R worker result), and the outcome (deterministic human-readable English or German). It distinguishes this from siblings like decode_uai_result by emphasizing human-readable output, making the tool's purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when a human-readable representation is needed, but it does not explicitly contrast with sibling tools such as decode_uai_result or compile_uai_context, nor does it state when not to use it. The usage context is implied but not explicitly guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.